Fast system identification algorithm for non-uniformly sampled noisy biomedical signal

The recently developed generalized linear least squares (GLLS) algorithm has been found very useful in non-uniformly sampled biomedical signal processing and parameter estimation. In this paper, the algorithm is used for the identification of a compartmental model with a pair of repeated eigenvalues based on the nonuniformly sampled noisy data. A case study is presented, which demonstrates that the algorithm is able to select the most suitable model for the system from the non-uniformly sampled noisy signals.